Exploring the Impact of DevOps Automation on the Reliability of Healthcare AI Software Delivery
Keywords:
DevOps, automation, healthcare AI, software delivery, reliability engineering, CI/CD, healthcare informaticsAbstract
The integration of DevOps automation into the delivery pipeline of healthcare AI software presents a transformative opportunity to enhance software reliability, reduce delivery cycles, and maintain compliance with regulatory standards. This study explores the relationship between DevOps automation practices and the delivery reliability of AI-based healthcare systems. Emphasis is placed on deployment frequency, incident rates, and time-to-recovery as reliability metrics. By comparing traditionally managed software lifecycles to those utilizing DevOps toolchains, we demonstrate notable improvements in operational stability and deployment predictability. Our findings are contextualized within the unique regulatory and ethical constraints of healthcare environments. The study contributes to both DevOps scholarship and healthcare informatics by offering empirical evidence and architectural models supporting automation-based software assurance.
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Copyright (c) 2025 Luna Enita (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
